Mobile devices such as cellular telephones, global positioning systems, and laptop computers are becoming increasingly popular through the world, and manufactures of these devices are constantly releasing new and improved devices that push the limits of technology. Today, many of these devices include microphones, accelerometers, cameras, positioning sensors, biometric sensors, and other sensing elements that may collect information about a user and/or a user's surroundings. For example, a positioning (e.g., GPS) sensor may determine a person's geographical location. Information collected from the positioning sensor may be combined with mapping software that provides some geographical context (e.g., what streets or restaurants are nearby). While this information is useful, its availability and relevancy is limited to the user and those with whom they explicitly share it.
To provide information more relevant to a larger community of many users as well as increase the coverage area, sensor networks are often deployed. Sensor networks are typically configured to measure a specific aspect of the physical environmental. For example, a sensor network may be deployed to monitor traffic on major highways near a large city or to monitor temperature or acoustics in an industrial complex. These sensor networks are often comprised of a plurality of sensor nodes (e.g., comprising sensor(s), local storage, a processor, and transceiver), that are positioned in particular areas of interests and are stationary during the collection process (e.g., the sensor nodes do not move while information is collected). The sensor nodes are configured to periodically transmit data to a computing system that collects and aggregates the data from the plurality of strategically placed sensor nodes. The aggregated data may then be used to provide information relevant to the larger community (e.g., how bad rush hour traffic is, how hot the building is, etc.).
While sensor networks, such as the one described above, have proven effective, there are significant limitations to these sensor networks. For example, the sensor nodes are often fixed and/or tethered to the environment so they cannot be easily moved and/or repositioned once they are put into place. Additionally, the sensor nodes are typically configured for one-way communication and are configured to measure only a predefined matrix (e.g., speed, temperature, heart rate, etc.). Therefore, the sensor network is not adaptable to changing interests of the community.